data integration of layers and features for the national map
DESCRIPTION
Data Integration of Layers and Features for The National Map. E. Lynn Usery Michael P. Finn Michael Starbuck. March 31, 2003. [email protected] [email protected] [email protected]. Outline. Motivation, Goals, and Objectives Approach Data Test Sites Methods Products Conclusions. - PowerPoint PPT PresentationTRANSCRIPT
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U.S. Department of the InteriorU.S. Geological Survey
Data Integration of Layers and Features for The National Map
March 31, 2003
E. Lynn Usery Michael P. FinnMichael Starbuck
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Outline
Motivation, Goals, and Objectives Approach Data Test Sites Methods Products Conclusions
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Motivation and Goals
The National Map will consist of integrated datasets, a digital product similar to the comprehensive, integrated lithographic printed map
Current USGS digital products (DLG, DOQ, NED, NHD, NLCD) are single layer and not vertically-integrated
The goal is to develop procedures for automated integration based on metadata
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Objectives
Framework for layer integration based on metadata
Framework for feature integration Example results for Atlanta and St. Louis
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Approach
Layer-based• Use existing seamless datasets• Determine integration feasibility based on resolution
and accuracy Feature-based
• Implement integration on feature by feature basis• Use developed feature library
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Data
Orthoimages from 133 Urban Areas National Hydrography Dataset (NHD) National Elevation Dataset (NED) Transportation (DLG) National Land Cover Dataset (NLCD)
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Data Integration Layer Sources
AccuracyResolutionTypeSourceNM Layer
2-10 m 30 mRasterNEDElevation13 m--VectorNHDHydrography1 ft1 ftRaster133 Urban AreasImages60 m30 mRasterNLCDLand CoverVarious--Vector133 Urban AreasTransportation
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Test Sites
St. Louis, Missouri• Initially the Manchester and Kirkwood quadrangles
Atlanta• Initial area in Northeast in Gwinnett County
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Methods
Layer integration• Determine compatible resolutions and accuracies and
use metadata to automatically combine appropriate datasets
• Determine transformations possible that integrate datasets of incompatible resolutions and accuracies
• Determine limits of integration based on resolution and accuracy
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Integration Possibilities
ToleranceFeature MatchingAccuracyData typesNeededNoPoint to pointSameVector/vector1YesPoint to pointsDifferentVector/vector2YesPoint to pointsSameVector/vector3YesPoints to pointsDifferentVector/vector4NoPixel to pixelSameRaster/raster5YesPixel to pixelDifferentRaster/raster6YesPixels to pixelSameRaster/raster7YesPixels to PixelDifferentRaster/raster8NoPixel to pointSameRaster/vector9YesPixel to point(s)DifferentRaster/vector10YesPixel to pointSameRaster/vector11YesPixels to pointsDifferentRaster/vector12
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Cartographic Transformations from Keates
Sphere to plane – projection• Mathematical, deterministic, correctable
Three-dimensional to two-dimensional• Mathematical, deterministic, correctable
Generalization• Non-mathematical, scale dependent, humanistic, not
correctable
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Mathematical Transformations -- Scale and Resolution Matching
If data meet NMAS, then integration can be automated based on the scale ratios
• If linear ratios of scale denominators are ½ , then integration is possible through mathematical transformations
• For ratios smaller than ½ , generalization results in incompatible differences
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Generalization Issues
Selection – common features may not appear on data layers to be integrated (Topfer’s Radical Law)
Simplification – lines may contain reduced numbers of points and have different shapes
Symbolization – for map sources, symbolization may result in areas shown as lines or points
Induction – features may have been interpolated and appear differently on different sources
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Feature Integration
Metadata exists on a feature basis• Accuracy, resolution, source are documented by feature• Use Feature Library with an integration application
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Products
Integration methodology for layers and features Test implementations for St. Louis and Atlanta
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Conclusions
Data integration of layers for The National Map can only be accomplished with datasets that are compatible in resolution and accuracy
Mathematical transformation can automate integration with limited ranges of scales, but cannot correct generalization differences between datasets
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U.S. Department of the InteriorU.S. Geological Survey
Data Integration of Layers and Features for The National Map
March 31, 2003
E. Lynn Usery Michael P. FinnMichael Starbuck